# Copyright 2022 Xilinx Inc.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
#     http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
#

import torch

from pytorch_nndct.nn.quantization.ops import round_ops

def quantize(tensor, scale, round_mode, min_v, max_v):
  round_fn = round_ops.get(round_mode)
  #return torch.min(torch.max(round_fn(tensor / scale) * scale, min_v), max_v)
  return torch.clamp(round_fn(tensor / scale) * scale, min_v, max_v)
